Feedback control systems have many applications, including temperature control, pressure control and so on. Feedback control systems maintain a controlled variable (e.g. temperature, speed, etc.) about a setpoint based on an error signal, namely the difference between the setpoint value and the actual value of the controlled variable. Control parameters of the feedback controller determine how the error signal is used to develop the feedback signal used to control the system. When a control system is first setup, the control parameters must be adjusted to provide acceptable responsiveness and accuracy of the feedback control system.
An example of a feedback controller is a proportional, integral, and derivative (PID) controller. The technique often used in the past to automatically adjust the parameters of a PID controller is to pass noise around the control loop and adjust the parameters so that the phase and amplitude of the noise coming through the loop is equal and opposite to the noise source. This technique works fine as long as the noise source is representative of the noise that disturbs the control loop when it is controlling the process. The degree to which the two noise sources are not equal is in some measure the degree to which the adjustment of the parameters is not optimal.
What is needed is an automatic tuning controller which provides an accurate estimation of controller parameters based upon the noise that actually disturbs the controlled process variable. It is further desirable that such estimation can be made in real time, while the controller is controlling the process. The method and apparatus should be applicable to both linear and non-linear controllers.